臺灣博碩士論文加值系統

在配電系統中，當雷擊、鹽害或人為引起之事故，導致系統發生電壓驟降，可能造成電力設備欠壓，保護電驛動作而造成電力中斷，或影響用戶端設備正常運轉，尤其對電力品質反應較靈敏之高科技產業受害最大。
本論文應用基因演算法於配電系統饋線重組之問題上，以降低系統的損失與電壓驟降，並加入模糊多目標規劃方法來求解。在本論文中亦利用一組簡化型的負載潮流方程組，以用來求解負載潮流問題，此分析方法可直接從線路末端計算至供電端，即可求解整個負載潮流資料，而摒除傳統方法於求解時所需之反覆疊代。此外，在基因演算法方面，針對配電系統之放射狀樹枝架構，利用Prufer number 葉片節點編碼方法於染色體的編碼上，使其在經歷交配、突變運算之後仍然能夠保持放射狀架構。
本文分別以一個16個匯流排與33個匯流排的配電系統，進行電腦模擬測試，其結果顯示本文所提之基因演算法，可有效地求得配電系統饋線重組之近似最佳解。

Voltage sags are usually caused by shorts circuits, overloads, and starting of large motors. The interest in voltage sags is mainly due to the problems they cause on several types of equipment: adjustable-speed drives, process control equipment, and computers.
In this thesis, a method based on the Genetic algorithms and decision making for multi-objective programming problems to study the reconfiguration in distribution systems for loss and voltage sag reduction is proposed. A set of simplified power flow equations is used for approximate loss calculation. Then the Prufer number is used for encoding a tree structure on the Genetic algorithms.
A 16-bus system and a 33-bus system are used as test systems for showing the applicability of the proposed method.

摘要..................................I
Abstract..............................II
誌謝..................................III
目錄..................................IV
圖目錄................................VII
表目錄................................IX
第一章 緒論...........................1
1.1 研究背景與動機....................1
1.2文獻回顧...........................2
1.3研究步驟...........................3
1.4研究目標...........................4
1.5本論文之貢獻.......................4
1.6論文架構概述.......................5
第二章 問題描述與數學表示式...........7
2.1 配電系統饋線重組問題..............7
2.2 配電系統負載潮流方程組............8
2.2.1 前言............................8
2.2.2 簡化型負載潮流方程組............9
2.3 電壓驟降之定義與成因..............13
2.3.1 前言............................13
2.3.2 電壓驟降之計算..................13
2.4 數學表示式........................15
2.4.1 最小化損失表示式................15
2.4.2 最小化壓降表示式................17
2.4.3 同時損失與壓降最小化表示式....19
第三章 數學背景.......................20
3.1 基因演算法之簡介..................20
3.2 基因演算法預備作業................21
3.2.1 適應函數........................21
3.2.2 Prufer number編碼與解碼方式.....21
3.2.3 初始族群........................27
3.3 基因演算法之工作原理..............27
3.3.1 染色體的複製(Reproduction)......28
3.3.2 染色體的交配(Crossover).........28
3.3.3 染色體的突變(Mutation)..........31
3.4 處罰函數(Penalty function)........31
3.5 模糊集合理論(Fuzzy set theory)....33
3.6 模糊線性規劃......................35
3.7 最佳化問題之求解過程..............38
第四章 模擬結果.......................39
4.1 十六個匯流排之模擬結果............39
4.1.1 以系統損失為單一目標............40
4.1.2 以壓降為單一目標................43
4.1.3 以系統損失與壓降同時進行雙目標規劃...45
4.2 三十三個匯流排之模擬結果..........49
4.2.1 以系統損失為單一目標............52
4.2.2 以壓降為單一目標................58
4.2.3 以系統損失與壓降同時進行雙目標規劃...61
4.3 模擬結果討論......................66
第五章 結論...........................67
參考文獻..............................68

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